Towards energy-efficient and robust disaster response networks

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

In the aftermath of a large-scale disaster (such as earthquake), existing communication infrastructures are often critically impaired, preventing timely information exchange between the survivors, responders, and the coordination center. Typically, a temporary network, called Disaster Response Network (DRN), is set up using smart devices, movable base stations and easily deployable cellular antennas. However, such networks are challenged by rapid devices' energy depletion and component failures due to environmental adversities and hardware faults. State-of-the-art literature address energy challenges through intelligent routing, however robustness of DRN against component failures is largely unaddressed. In this paper, we investigate designing a novel network topology for DRNs, which is both energy-efficient and robust against component devices' failures. Specifically, the objective is to construct a sparse structure from the original DRN (termed, Sparse-DRN) while ensuring that there exists a connected tree backbone. Our performance evaluation shows that the Sparse-DRN offers a good trade-off between the energy efficiency and network robustness, while ensuring the QoS requirements i.e., packet delivery and network latency.

Original languageEnglish
Title of host publicationICDCN 2019 - Proceedings of the 2019 International Conference on Distributed Computing and Networking
Pages397-400
Number of pages4
ISBN (Electronic)9781450360944
DOIs
StatePublished - Jan 4 2019
Event20th International Conference on Distributed Computing and Networking, ICDCN 2019 - Bangalore, India
Duration: Jan 4 2019Jan 7 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference20th International Conference on Distributed Computing and Networking, ICDCN 2019
Country/TerritoryIndia
CityBangalore
Period1/4/191/7/19

Bibliographical note

Publisher Copyright:
© 2019 Association for Computing Machinery.

Funding

This work is partially supported by NATO grant G4936 and Intelligent Systems Center (ISC) at Missouri S&T, Rolla.

FundersFunder number
Division of Information and Intelligent Systems
North Atlantic Treaty OrganizationG4936

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

    Keywords

    • Disaster Response Network
    • Energy efficiency
    • Robustness

    ASJC Scopus subject areas

    • Software
    • Human-Computer Interaction
    • Computer Vision and Pattern Recognition
    • Computer Networks and Communications

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